The process of “converting” 2D photographed images into three-dimensional 3D stereo images (left eye and right eye pairs) for the motion picture and television industry is extremely labor intensive, time consuming, financially expensive, and has the added problem of being geometrically inaccurate to the original scene.
Current technologies allow for the creation of 3D stereo imaging from 2D photography. However, the available 3D technologies do so through interpretive and creative means, or through system configurations that do not capture the true depth and geometry of the original environment using the 2D photography. For example, a conventional and popular technology used to make a 3D stereo image (or a 3D movie, which is a sequence of 3D stereo images) is to use two cameras separated by the typical human interocular distance DH (i.e., human eye spacing), which is assumed in the industry to be about 68 mm, though smaller distances DH are often used for reasons described below. The two cameras are then oriented (angled) so that their fields of view converge and overlap at a distance DS where the various objects in the scene being filmed are located. While this allows for creation of a 3D effect, the actual image-capture process does not collect a substantial amount of true 3D information for the given scene mainly because the interocular distance DH is too small relative to the distance DS. Said differently, the amount of spatial (3D) data captured by such an arrangement is far smaller than the actual 3D volume of the scene being imaged.
This lack of accurate volumetric data and true 3D geometry provides significant problems and challenges when visual effects such as computer-generated elements need to be added to the photographed or filmed scenes. Complex visual effects scenes in 3D stereo that incorporate live action captured using a conventionally two-camera 3D imaging system require critical stereo decisions to be made at the time of filming, such as the aforementioned convergence angles and interocular distances.
In addition, certain types of image post-processing require the full 3D spatial data to be captured to facilitate removing artifacts in the captures scene. For example, in movies it not uncommon to have to remove an unwanted jet contrail from an outdoor scene. In 2D movie (cinemagraphic) post-processing, this is a straightforward operation. However, in 3D movie post-processing, the jet contrail is also in 3D and thus is much more difficult to remove.
Because of the limitations of present-day 3D imaging technology, critical 3D-stereo-related decisions must made at the time of shooting rather than in post-production. However, it would be much preferred to be able to make such decisions in post-processing to optimize the camera positions relative to the surrounding cuts of the film. The addition of visual effects in the form of computer-graphics (CG) environments and CG characters into scenes that have been originally shot in 2D and converted into 3D stereo further complicates matters and poses great technical and financial challenges to visual effects post-production.
It would thus be of tremendous benefit to be able to reduce the time and expense presently associated with adding CG environments and CG characters to a 3D stereo movie as part of the movie post-processing.